Getting Started in HPLC

Section 2F. HPLC Data Systems

   
A chromatography data system is essentially a computer running specialized software designed to integrate chromatographic peaks and relate peak area or height to the amount of analyte present on the basis of calibration data. In many cases, the software will include additional statistical and database capability for enhanced analysis, storage, and reporting of information.


 
In its most fundamental form, a chromatogram is simply a plot or record of a voltage signal as a function of time. In a properly functioning UV detector (for example), this voltage is directly proportional to the absorbance of the effluent in the detector cell. Assuming that the Beer-Lambert law holds, this absorbance will be directly proportional to the concentration of the absorbing species (the analyte); this means that the chromatogram is (indirectly) a plot of sample concentration versus time. Assuming that the mobile phase flow through the detector is constant, the volume of mobile phase pumped will be directly proportional to the elapsed time. Thus, the chromatogram is (even more indirectly) a representation of concentration versus volume. Measuring the area under the peak amounts to measuring the product of concentration times volume, which is proportional to the mass (or moles) of analyte.


 
The term "integration" refers to the process of measuring the area included under a chromatographic peak. This is accomplished by adding the voltage measurements made at equal time intervals from the beginning to the end of the peak, then subtracting a "correction trapezoid" to correct for the offset of the chromatographic baseline from true zero as well as baseline drift.

 

Integration is carried out by summing voltage measurements made from the beginning to the end of the peak then subtracting the area of a correction trapezoid to account for non-zero baseline.


   
In order to accomplish this task, the data system software must be able to:
  • damp out or otherwise ignore random fluctuations in the signal ("baseline noise")
  • identify the beginning of a peak
  • identify the peak maximum (the retention time of the peak)
  • identify the end of the peak
  • compute the area of the correction trapezoid.


 
   
Noise reduction can be accomplished by either ignoring baseline fluctuations smaller than a selected threshold or "time averaging" the signal to damp out random fluctuations. Although the threshold values or sampling rates can be set manually, most data systems include some sort of "auto tune" capability which sets the appropriate parameters on the basis of an actual measurement of baseline noise when the mobile phase is flowing but before the sample has been injected.

Likewise, the "slope sensitivity" values for the beginning and ending of the peaks can be automatically determined in most cases.


 

   

 
   
Modern data systems will either draw the calculated baselines or else use markers to indicate the beginning and end of peak integration. In most cases, the user can manually "force" a baseline when the computer algorithm is obviously in error (the human eye is surprisingly good at pattern recognition!), but such manual intervention should be avoided if possible in order to avoid the potential for biased results.

The figure at the right shows three "predictable" types of erroneous baseline assignments (dotted lines) along with the correct integration of the peaks (red shading).


   
If the width of a peak is constant from one chromatogram to another (this is usually the case), then peak height may be used as a surrogate for peak area. Peak height measurements are more reliable for very small peaks or for chromatograms in which resolution is marginal. Peak area is preferred for very large peaks or where a wide linear range is required.


 

   
 

 


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Last revised: April 06, 2001.